The following relates generally to medical imaging and patient monitoring. It finds particular application in conjunction with continuous patient movement monitoring of potential delirium patients, and will be described with particular reference thereto. However, it will be understood that it also finds application in other usage scenarios and is not necessarily limited to the aforementioned application.
Movement can provide information about a patient's state and wellbeing. For example, delirium is a common acute disorder affecting many adults in hospitals and can be identified by specific movements such as grabbing in the air, pinching skin, or repetitive and continuous head, arm or leg movements. Other patient movements can indicate a change in patient status and/or emergency such as falling out of a bed, getting out of bed, pulling at or on medical equipment, etc. Patient movements are typically analyzed by sporadic observation of healthcare practitioners which may miss movements and corresponding changes in patient conditions. For example, the sporadic observation by healthcare practitioners introduces a non-negligible lag in the detection of critical problems such as delirium.
A previous approach to patient movement monitoring included the use of an on-body wrist sensor or accelerometer. The presence of the on-body wrist sensor or other body worn sensor can be disturbing to a patient. The wrist sensor does not capture movements performed by other body parts. The wrist sensor does not allow identification of higher-level interpreted movements such as “pinching skin”, “grabbing air”, pulling on medical equipment, falling out of bed, getting out of bed, etc.
Several factors complicate an approach based on continuous analysis of video of the patient. One factor is the recognition of the patient and the identification of the patient's body parts separate from the many possible environments. The recognition of the patient and the identification of body parts can be further complicated by the presence of a covering such as a blanket, which may obscure direct observation of body parts. Another factor may be the intermittent presence of visitors or healthcare practitioners which may obscure or overlap portions of the patient's anatomy visible to video. Another complicating factor is changes in lighting.
The following discloses a new and improved automatic continuous patient movement monitoring which addresses the above referenced issues, and others.